CNN has proven a last-breaking performance in various fields, such as object recognition, and has also gained more attention in brain imaging, especially in tissue and brain segmentation. In this paper, an automated technique for MS lesion segmentation is proposed, which is built on a 3D patch...
2 Related Hard-lable Attack 作者首先简单回顾一下针对CNN的hard-label attack: Boundary Attack:以高斯噪声初始化,每次沿两个方向移动:soucre direction和spherical direction,公式描述为:xnew∗=x∗+δ⋅η||η||2+ϵ⋅x−x∗||x−x∗||2,η∼N(0,I) 其中eta为spherical direction,δ为...
The recent advances in Vision Transformer (ViT) have demonstrated its impressive performance in image classification, which makes it a promising alternative to Convolutional Neural Network (CNN). Unlike CNNs, ViT represents an input image as a sequence of image patches. The patch-wise input image ...
through a CNN classifier (Ciresan et al. 2012). Doing this for each pixel produces the segmente...
Our proposed method outperforms solutions based on known CNN architectures on the same dataset, achieving a lower Mean Absolute Error (MAE) with fewer parameters. This demonstrates the effectiveness of our approach in accurately counting plants in agricultural fields. 展开 ...
PPformer, for low-light image enhancement. PPformer is a CNN-transformer hybrid network that is divided into three parts: local-branch, global-branch, and Dual Cross-Attention. Each part plays a vital role in PPformer. Specifically, the local-branch extracts local structural information using a...
Deep learning with convolutional neural networks (CNN) has achieved unprecedented success in segmentation, however it requires large training data, which is expensive to obtain. Active Learning (AL)...doi:10.1007/978-3-030-00889-5_10Jamshid Sourati...
CNN‐based systems perform very well on intra‐data set experiments, yet they fail to generalise to the data sets that they have not been trained on. This indicates that they tend to memorise data set‐specific spoof traces. To mitigate this problem, the authors propose a Deep Pat...
building change detectionconvolutional neural networks (CNNs)deep learningpatch-wisepixel-wiseBuilding change detection (BCD) is crucial for sustainable urban development and operational efficiency. High-resolution remote sensing imagery offers numerous benefits for this task. However, it also presents ...
The proposed model outperformed when compared with state-of-the-art CNN-based models, i.e., ResNet-50 and VGG-16.Arshed, Muhammad AsadMumtaz, ShahzadIbrahim, MuhammadDewi, ChristineTanveer, MuhammadAhmed, SaeedComputers (2073-431X)